Inspiration

150 million people worldwide use Airbnb when searching for travel accommodations. How many of those people automatically check Airbnb as their default without ever comparing hotels nearby? While many people assume Airbnb has the lowest accommodation prices, in many places hotels are actually cheaper and/or provide a better experience than renting an Airbnb. We're deal hunters at our core and we wanted to make travel planning easy by enabling multiple sources of travel data in one place to get the best deals and experiences with the least amount of effort while planning the perfect dream vacation or that recurring work related trip.

Enter Air Compare - the one stop shop travel planning Chrome extension that allows users to:

• Compare hotels near the Airbnb listing they're considering

• Get average car rental prices based on when you’re renting a car

• Get estimated ride sharing (Lyft) prices to their destinations

We wanted to provide users with the best accommodation deals but more importantly, we also wanted to solve the "last mile problem" (getting people from a transportation hub to their final destination) as it relates to travel. Often transportation costs end up adding up significantly and it’s difficult when planning a trip to estimate those costs ahead of time. We wanted to bring transparency to this area so there’s no hidden surprises when it comes time to travel, only #unforgettableexperiences.

What it does

We've built a seamless, multi-faceted Chrome extension that gives users peace of mind that they're getting the best deals while saving them countless hours of searching multiple different sites and apps (because each hour saved is another hour to watch funny cat videos #priorities).

At its very basic function, Air Compare will automatically populate hotels within an Airbnb's vicinity and in a similar price range (+/- $50) and users can filter by distance and price. Users can also review each hotel's amenities so they can make the best choice based on what's important to them when travelling, with a point of comparison against what Airbnbs offer.

For those more sophisticated travelers who like to plan in advance (my Virgo perfectionists, I'm talking to you!) and know their itinerary, they can go to Add Trip Details to enter in a destination address (such as their client's office or a tourist destination they'll be visiting) and also search for car rental and ride sharing prices to/from their destination.

Air Compare allows users to:

  1. Compare multiple hotels near the Airbnb listing they're considering with information on:
    • Distance from the hotel to the Airbnb with the ability to sort by distance or price
    • Price per night
    • Hotel amenities (users can compare the Airbnb amenities with hotel amenities to determine what's truly important to their trip; a hot tub time machine may be crucial when scaling Mount Everest but not so crucial on a Safari adventure in Africa)
    • Filter and sort by rewards points and/or price for programs like the Starwoods Preferred Guest loyalty program without having to check yet another site
  2. Determine whether renting a car or using ride sharing is the better choice:
    • Get average car rental prices (based on the nearest airport the Airbnb is closest to)
    • Get Lyft estimates from the airport to the Airbnb AND each nearby hotel
    • Get Lyft estimates and travel times to a destination for both the Airbnb listing AND each nearby hotel (because we're overachievers like that!)
    • Users can now compare at a glance how much their car rental vs. using ride sharing will cost without guessing or doing any extra work

How we built it

  • DataGrid
  • Javalin
  • OpenJDK
  • Kotlin
  • Node (Scraper)
  • Javascript
  • Chrome extension
  • Sabre API
  • Lyft API
  • Amadeus API
  • Lufthansa API
  • Google Geo API
  • Fuel

Video demo of the technical features: https://youtu.be/KncPJEdiSSg.

Challenges we ran into

• Restricted access to travel APIs (with more functionality)

• No consistent API that offered us exactly what we needed so we had to rely on a host of different travel related APIs, such as Sabre, Amadeus, Lufthansa etc. There was no Starwoods API either so we had to write our own scraper which we turned into a microservice and deployed on OpenShift

• Unfamiliarity with OpenShift so there was a learning curve but once we got the hang of it, it was really great to use

Accomplishments that we're proud of

Everything! Air Compare allows you to compare Airbnb listings with nearby hotel searches but it also does so much more. By hooking in car rental prices, ride share (Lyft) estimates including travel time, hotel loyalty points programs and hotel amenities, it truly gives travelers the tools they need to create an amazing travel experience. There are countless sites and services that aggregate one facet of the travel experience, such as hotel or car, but we’re giving users insight into numerous areas that affect their trip in just one simple Chrome extension.

What we learned

• Most people don’t search both Airbnb and hotel listings to compare because it’s too time consuming and a hassle

• Contextual information is hugely important – providing one source of info (car rental prices) is useful but doesn’t provide a meaningful source of data until paired with its alternative (ride sharing costs) so users can make an informed decision and be confident in their choice

• There are a lot of travel APIs and it requires work to stitch everything together to create a meaningful tool

What's next for Air Compare

• Partner with travel sites such as Amadeus, Expedia and Lyft and enable direct booking for hotels, car rentals, flights etc from our site to drive more revenue and growth to our partners.

• Build more features that make it even easier for users to compare numerous aspects of their travel experience (e.g. other home sharing sites, star rating information, reviews, Yelp integration to search restaurants, coffee shops etc nearby)

• Because we’re also collecting a lot of travel data from users, all our partners (Sabre, Lyft Amadeus, Expedia, etc) could benefit from our data and run targeted promotions based on the fluctuation of the travel economy. E.g., if we share data that lets Lyft know there will be a large number of travelers to an area at one time, they could push offers to their users for discounts on rides in that city, or send a call out to their drivers to have more drivers in that area.

• Data is king and we’re not only driving more customers to our partners but also giving them rich data that they could use to grow and very specifically target customers/run campaigns.

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